This research develops a framework to recover missing or broken electricity records, verify that campus energy data is accurate, and uncover patterns in how university buildings consume power over time.
This project develops an AI-driven robotic platform that uses multispectral sensing to inspect and monitor power transmission lines.
This research develops a hybrid scanning trajectory designed for high-quality magnetic and optical imaging systems.
This project develops an AI-driven robotic platform that uses multispectral sensing to inspect and monitor power transmission lines.
This research combines probabilistic and federated AI forecasting with advanced optimal control to support wind-power development in Kazakhstan.
This project develops AI-based optimization and energy-management methods for wind-solar hybrid microgrids supporting Kazakhstan’s green energy transition.
This research focuses on improving the sensitivity and image quality of Magnetic Particle Imaging for targeted cancer diagnosis and treatment applications.
This project investigates optimized scanning paths to improve reconstruction performance and image quality in Magnetic Particle Imaging systems.
This project focused on designing low-speed, high-torque permanent-magnet motors for collaborative robotic systems.
This research developed an adaptive optimization framework for improving energy efficiency in cloud-computing environments.
This project studied optimization and control methods for integrated renewable-energy conversion systems.
This research developed high-performance control systems for interior permanent-magnet synchronous motors used in electric vehicles.
This project developed optimal-control approaches for performance, efficiency, and reliability in industrial applications.